Chemical Exchange Saturation Transfer (CEST) imaging has been attracting attention due to its unique characteristics: 1) the ability to detect signals from low concentration species based on the highly selective saturation of rapidly exchanging spins and 2) the capability of detecting changes in environmental parameters in vivo including: pH, temperature and ion concentration. There have been a number of pre-clinical and now also clinical applications which involve either the detection of administered or endogenous CEST agents. A theme of many of these studies involves applying CEST imaging to cancer for characterization of tumor vasculature, metabolism, extracellular pH and nanocarrier uptake.
In order to detect CEST contrast, it is common practice to increment the frequency of a saturation pulse across a range of frequencies. The simple and most common method to detect and quantify CEST contrast is by calculating the asymmetry in the magnetization transfer ratio (MTRasym) at the frequency of the exchangeable protons (Δω):
      MTR    asyn    =            (                        S          ⁡                      (                                          -                Δ                            ⁢                                                          ⁢              ω                        )                          -                  S          ⁡                      (                                          +                Δ                            ⁢                                                          ⁢              ω                        )                              )              S      0      which is the subtraction of the two water signal intensities with saturation pulse at +Δω and −Δω with respect to water, S(+Δω) and S(−Δω), normalized by the signal without saturation (S0), or by S(−Δω) to amplify the dynamic range. Tumors and strokes display contrast on MTRasym maps at saturation offsets between 1-3.5 ppm from water, an effect that has been connected to the amide protons of extra soluble peptides/proteins found in brain tumors which resonate around 3.5 ppm from water, or changes in pH and has been termed Amide Proton Transfer (APT). The amount of APT signal produced by brain tumors was shown to correlate with histopathological grade in patients on clinical 3T scanners, and was also shown to be a marker that could differentiate tumor recurrence from radiation necrosis. There are also attempts to monitor tumor response to HIFU and chemotherapy.
Although CEST imaging has shown great potential for oncological imaging, there are obstacles towards widespread application, including the low Contrast-Noise-Ratio (CNR) of the images, low specificity, sensitivity to field inhomogeneities, and susceptibility to interference from other sources of contrast. In addition, collection of CEST images can be quite time-consuming. A typical scheme for a CEST pulse sequence is shown in FIG. 1A. Before the water signal readout, a long frequency-selective continuous wave (CW) pulse or pulse train is applied at the resonance frequency of the agent to prepare the magnetization. The Saturation Preparation (Sat. Prep.) pulse(s) is usually on the order of seconds in order to obtain sufficient amplification of signal loss through multiple exchanges of saturated solute protons with water, i.e. low-concentration saturated solute protons are replaced by unsaturated water protons and the new protons are saturated. In addition, for most in vivo data the MTRasym value is not purely CEST contrast, but also includes interference from other sources of water signal loss generated by the saturation pulse, including conventional magnetization transfer contrast (MTC), direct saturation (DS) and relayed Nuclear Overhauser Effect (NOE) transfers. Finally, most endogenous CEST agents resonate between 1-4 ppm from water leading to low specificity for CEST measurements.
Because of the challenges mentioned above, new methods are needed which improve the specificity of CEST measurements or reduce image acquisition times. Recently several acquisition methods have been developed including methods to suppress MTC such as SAFARI, Two-frequency and VDMP and sequences for extracting components of exchange contrast e.g. CERT, Spin-Lock and FLEX. There are also sequences for accelerating CEST data acquisition, such as using RARE or FLASH, CEST-FISP, steady-state methods for fast 3D brain imaging of APT and recently methods based on gradients applied during saturation can push the speed of Z-spectrum collection to single-shot. Gradient-encoded offset methods are intriguing, but currently only have been demonstrated in vitro and might be very challenging in vivo due to inhomogeneous distribution of contrast.
One proposed strategy for improving CEST image specificity acquires multiple STw images with different saturation lengths (tsat) to add another dimension of information describing the decay in the water signal. Saturation length can also be referred to as duration and time. In simple phantoms (CEST agent in water/PBS), the changes in MTRasym as a function of saturation length (tsat) can be used to measure exchange rates (Ksw), otherwise known as QUEST. In vivo, this Length and Offset VARied Saturation (LOVARS) data can be studied to separate tumor pixels from control brain tissue through the different tsat-dependence of MTRasym values. FIG. 1B illustrates a graphical view of an acquisition scheme for LOVARS image acquisition. Based on the knowledge that CEST, DS and MTC behave differently as a function of tsat, DS and MTC are predominantly symmetric around the water resonance (CEST is asymmetric), the LOVARS imaging scheme acquires a series of images consisting of N groups of LOVARS' Units (LUs) with 4 images in each LU. The pattern of images collected and the resulting signal is given by the following expression:
                                                                        S                LOVARS                            =                            ⁢                                                [                                                            S                      1                                        ,                                          S                      2                                        ,                                          S                      3                                        ,                                          S                      4                                                        ]                                                                      n                    =                    1                                    ,                  2                  ,                                                                          ⁢                  …                  ⁢                                                                          ,                  N                                                                                                        =                            ⁢                              [                                                      S                    ⁡                                          (                                                                                                    -                            Δ                                                    ⁢                                                                                                          ⁢                          ω                                                ,                                                  T                                                      sat                            ⁢                                                                                                                  ⁢                            2                                                                                              )                                                        ,                                      S                    ⁡                                          (                                                                                                    -                            Δ                                                    ⁢                                                                                                          ⁢                          ω                                                ,                                                  T                                                      sat                            ,                                                                                                                  ⁢                            1                                                                                              )                                                        ,                                                                                                                                        ⁢                                                      S                    ⁡                                          (                                                                                                    +                            Δ                                                    ⁢                                                                                                          ⁢                          ω                                                ,                                                  T                                                      sat                            ⁢                                                                                                                  ⁢                            2                                                                                              )                                                        ,                                      S                    ⁡                                          (                                                                                                    +                            Δ                                                    ⁢                                                                                                          ⁢                          ω                                                ,                                                  T                                                      sat                            ⁢                                                                                                                  ⁢                            1                                                                                              )                                                                      ]                                                              n                  =                  1                                ,                2                ,                                                                  ⁢                …                ⁢                                                                  ,                N                                                                        [        6        ]            where S(−Δω, Tsat,2) represents the signal for an image with the saturation pulse at frequency=−Δω and of length=Tsat,2. Two different saturation offsets are used: 1) +Δω, on resonance with the exchangeable amide protons and 2) −Δω, on the opposite side of water from the exchangeable protons, and two different tsat's, a longer one (Tsat,1) and a shorter one (Tsat,2).
This data can discriminate the different levels of interference from MTC, DS and NOE, through collecting tsat-dependence information and increase CNR and the specificity of CEST imaging. Unfortunately, it is not practical to acquire images with multiple tsat's and also with multiple saturation offsets (Z-spectra) due to long scan times, although both of them are useful for improving the CEST imaging. FIG. 1C illustrates a graphical view of an acquisition scheme for MeLOVARS. Instead of employing a single long Sat. Prep. module of length tsat (i.e. >1 sec.) before echo readouts, the Me-LOVARS method divides this Sat. Prep. into N=3-10 sub-modules, each with a length of tsat/N (˜0.3 sec. −1 sec.), and in between inserts a low flip-angle (FA=α) fast gradient echo read-out sequence (here EPI), followed by a flip back pulse (FA=−α) for retaining longitudinal magnetization, as illustrated in FIG. 1C. This method could further be improved to allow for better discrimination between various CEST imaging agents.
It would therefore be advantageous to provide an efficient and effective form of CEST magnetic resonance imaging, which enables improvement of the image contrast-to-noise ratio, image specificity and agent quantification in vitro and in vivo.